Preparation¶

SARvey requires a coregistered stack of SLC and the related geometry information in the MiaplPy data format. The coregistered stack of SLC can be created using an InSAR processor, such as ISCE, GAMMA, or SNAP. Currently MiaplPy only supports ISCE. Support for GAMMA and SNAP is planned for future. After creating the coregistered stack of SLC, run the “load_data” step from MiaplPy to create the “inputs” directory which contains “slcStack.h5” and “geometryRadar.h5”.

Preprocessing¶

ISCE¶

… ISCE brief processing to be added

The ISCE products should have the following directory structure that is later in Loading Data into MiaplPy step.

ISCE_processed_data
├─ reference
│   ├─ IW*.xml
│   └─ ...
├─ merged
│   ├─ SLC
│   │   ├─ YYYYMMDD
│   │   │   ├─ YYYYMMDD.slc.full
│   │   │   └─ ...
│   │   ├─ YYYYMMDD
│   │   ├─ YYYYMMDD
│   ├─ geom_reference
│   │   ├─ hgt.rdr.full
│   │   ├─ lat.rdr.full
│   │   ├─ lon.rdr.full
│   │   ├─ los.rdr.full
│   │   └─ ...
└─ baselines
    └─ YYYYMMDD_YYYYMMDD
        └─ YYYYMMDD_YYYYMMDD.txt

GAMMA¶

Support is in progress.

SNAP¶

Support is planned for future.

Loading Data to MiaplPy Format¶

Loading Data into MiaplPy¶

Run the load_data step of MiaplPy to convert the preprocessed stack of SLC to slcStack.h5 and geometryRadar.h5. Refer to MiaplPy instruction on how to prepare the stack of coregistered SLC and modify the template file.

miaplpyApp miaplpy_template_file.txt --dostep load_data

The output includes the following directory structure that is later used as input in SARvey processing:

inputs
  ├── slcStack.h5
  └── geometryRadar.h5

Check the data¶

Use info.py from MintPy to check the files’ information.

info.py inputs/slcStack.h5
info.py inputs/geometryRadar.h5

Use view.py from MintPy to visualize the files and make sure they look fine.

view.py inputs/slcStack.h5
view.py inputs/geometryRadar.h5

Optional Steps¶

Phase Linking¶

This step is optional. You can run it if you wish to perform distributed scatterers (DS) analysis. Caution: This step is computationally heavy and might be time-consuming for large datasets.

miaplpyApp miaplpy_template_file.txt --dostep phase_linking
 miaplpyApp miaplpy_template_file.txt --dostep concatenate_patches

The output includes the following directory structure that is later used as additional input in SARvey processing if the config file is modified to inclued DS analysis.

MiaplPy working directory
├─ inverted
│   ├── phase_series.h5
│   ├── ...
├── maskPS.h5
└── ...

Subset Data¶

Data loaded into MiaplPy can be subset using Mintpy’s subset function. This is particularly useful if you have a dataset in MiaplPy format and want to crop a small area of it. Both slcStack.h5 and geometryRadar.h5 should be subset with the same range and azimuth coordinate ranges. Also the Phase Linking results (phase_series.h5 and maskPS.h5) should be subset if it has been created. Please refer to Mintpy for more instruction to subset. Run subset.py -h for information about parameters. The following example crops the data between 500 and 800 in range and 100 and 1000 in azimuth coordinates.

subset.py -h

subset.py inputs/slcStack.h5 -x 500 800 -y 100 1000 -o inputs_crop/slcStack.h5
subset.py inputs/geometryRadar.h5 -x 500 800 -y 100 1000 -o inputs_crop/geometryRadar.h5

subset.py inverted/phase_series.h5 -x 500 800 -y 100 1000 -o inverted_crop/phase_series.h5
subset.py maskPS.h5 -x 500 800 -y 100 1000 -o inverted_crop/maskPS.h5

Check the data after subsetting it and make sure all products look correct.

Create Manual Mask¶

A mask can be created manually using MintPy’s generate_mask.py tool. This is particularly useful if you want to limit the MTInSAR processing to certain areas. Run generate_mask.py -h for information about parameters. The following example allows to draw a polygon on top of the DEM to create a mask.

generate_mask.py -h

generate_mask.py inputs/geometryRadar.h5 height -o mask.h5 --roipoly         # draw polygon on top of the DEM

Alternatively, a mask can be drawn on top of the temporal coherence map, in case step 0 (preparation) of sarvey has been executed already.

generate_mask.py results_dir/temporal_coherence.h5 -o mask.h5 --roipoly         # draw polygon on top of the temporal coherence image

Follow the instructions in the terminal:

Select points in the figure by enclosing them within a polygon. Press the ‘esc’ key to start a new polygon. Try hold to left key to move a single vertex. After complete the selection, close the figure/window to continue.